Payment Reconciliation & Matching

Payment Reconciliation — Get Engine Script (large exports)

payment_reconciliation_get_engine

Read-only

For more than 5,000 receipts or bank lines, or 20,000 open items / ledger / GST rows, or any such file already in your code sandbox. Returns a complete numpy-only Python script with the same engine as payment_reconciliation; it reads the receipts, open items, bank lines, ledger, GSTR-2B and purchase register files, prints the decision cards and counts, and writes every match, exception and the updated rules to reconciliation.json. No financial data reaches this server on this path.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "payment_reconciliation_get_engine"
  }
}

Input Schema

Name	Required	Description
`params`	No	Other inputs exactly as payment_reconciliation takes them (side, as_of ...).
`receipts_path`	No	receipts file in your sandbox (CSV/TSV/JSON).
`bank_lines_path`	No	bank_lines file in your sandbox (CSV/TSV/JSON).
`open_items_path`	No	open_items file in your sandbox (CSV/TSV/JSON).
`gstr2b_rows_path`	No	gstr2b_rows file in your sandbox (CSV/TSV/JSON).
`ledger_entries_path`	No	ledger_entries file in your sandbox (CSV/TSV/JSON).
`rules_snapshot_path`	No	rules_snapshot JSON from an earlier run.
`confirmed_matches_path`	No	confirmed_matches file in your sandbox (CSV/TSV/JSON).
`purchase_register_path`	No	purchase_register file in your sandbox (CSV/TSV/JSON).

Output Schema

Name	Required	Description	Default
`notes`	No
`paths`	No
`script`	Yes
`language`	No
`requires`	No
`writes_file`	No
`instructions`	Yes
`engine_version`	Yes
`scipy_required`	No
`data_requirements`	No
`network_access_required`	No

Schema Changelog

Changes observed during successful MCP inspections.

First observedOct 30, 2026

TDQS

A4.4/5.0

Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true and destructiveHint=false, but the description adds genuinely new behavior: the tool returns code rather than doing the work, that code reads six named file types, prints decision cards/counts, and writes matches, exceptions and updated rules to reconciliation.json. The privacy note that no financial data reaches the server is material context an agent could not infer.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, front-loaded with the numeric thresholds that determine selection, followed by what the returned script does. Dense but nearly every clause carries selection-relevant information; the enumerated file list is slightly redundant with the schema.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a nine-parameter, nested-object, no-required-field tool with an output schema, the description covers the trigger condition, the nature of the return value (executable script, not data), the artifacts it produces, and the data-residency guarantee. An agent has everything needed to choose and invoke it correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so every path parameter is already documented as a sandbox CSV/TSV/JSON file, and the nested params object points back to payment_reconciliation. The description lists the same file categories but adds no format, size or precedence semantics beyond the schema — baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource — returns a complete numpy-only Python script running the same engine as payment_reconciliation — and immediately scopes it to oversized datasets. The size thresholds distinguish it cleanly from the sibling payment_reconciliation without needing the schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives concrete trigger conditions: >5,000 receipts/bank lines, >20,000 open items/ledger/GST rows, or files already sitting in the sandbox. The alternative (payment_reconciliation) is named and its equivalence stated, so the when-not is strongly implied by the thresholds even if never spelled out.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All Payment Reconciliation & Matching tools Inspect

Try in Browser

One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.